Nutrition Knowledge and Practices of Varsity Coaches at a Canadian University
Bibliographic record
Abstract
PURPOSE: Coaches' sports nutrition knowledge and subsequent nutrition recommendations can have an impact on athletes' health and performance. The purpose of this study was to determine sports nutrition knowledge and nutrition recommendation practices of varsity coaches at one Canadian university and to determine if the coaches' nutrition knowledge influenced nutrition recommendations to athletes. The coaches' accessibility to sports dietitians was also examined. METHODS: Coaches (n = 5) completed a modified psychometrically validated nutrition knowledge questionnaire and a semi-structured interview. Mean scores were calculated for questionnaire answers based on the correct answer and the coach's degree of certainty in their answer. Interviews were analyzed using thematic analysis. RESULTS: Results showed a low nutrition knowledge, yet all coaches made nutrition recommendations to their athletes for fluid needs, dietary supplementation, and weight management; areas that may be potentially detrimental to the health of athletes. In addition, they made recommendations with regard to fluid needs, training diet, precompetition diet, recovery diet (i.e., post training or competition), dietary supplementation, and weight management; areas that could have potentially negative performance consequences to the athlete. CONCLUSIONS: It was determined that coaches had low nutrition knowledge scores and still made nutrition recommendations to athletes. The importance of sports dietitian involvement in varsity athletics is emphasized.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".